Download PDF
Hanson Distillery Partners with Samsara to Automate Quality Checks for Premium Vodka Production
Technology Category
- Analytics & Modeling - Computer Vision Software
- Functional Applications - Manufacturing Execution Systems (MES)
Applicable Industries
- Food & Beverage
Applicable Functions
- Quality Assurance
Use Cases
- Predictive Quality Analytics
- Machine Condition Monitoring
Services
- System Integration
- Software Design & Engineering Services
The Challenge
The Hanson family, owners of Hanson of Sonoma, a premium craft vodka distillery, faced significant challenges in maintaining the high quality and precise packaging of their award-winning products. Their commitment to quality required rigorous quality checks, especially for label placement and fill levels, which were manually intensive and inefficient. The production process involved six labels on each bottle, with exact placement and height requirements for the cork and labels. This manual process was time-consuming and prone to errors, making it difficult to scale production efficiently without compromising on quality.
About The Customer
Hanson of Sonoma is a family-owned, artisanal spirits company based in California's Wine Country. The company specializes in producing premium, organic, grape-based, gluten-free, and non-GMO vodka. The Hanson family has built a reputation for their commitment to quality and innovative approach to spirits, which has led to their products being featured in high-end restaurants, national retail chains, and winning numerous awards. The family-run business is deeply involved in every aspect of production, ensuring that their values and standards are upheld in every bottle they produce.
The Solution
To address their quality control challenges, Hanson of Sonoma partnered with Samsara to implement machine vision technology for automating the quality checks of label placement and fill levels on their production line. This technology allowed them to ensure the accuracy and consistency of their packaging without the need for manual intervention. By automating these processes, the Hansons were able to increase production efficiency while maintaining their high standards of quality. The implementation of Samsara's machine vision technology provided a more economical, cleaner, and efficient solution for their quality control needs, enabling them to focus on scaling their production without compromising on the exceptional quality of their products.
Operational Impact
Related Case Studies.
Case Study
The Kellogg Company
Kellogg keeps a close eye on its trade spend, analyzing large volumes of data and running complex simulations to predict which promotional activities will be the most effective. Kellogg needed to decrease the trade spend but its traditional relational database on premises could not keep up with the pace of demand.
Case Study
HEINEKEN Uses the Cloud to Reach 10.5 Million Consumers
For 2012 campaign, the Bond promotion, it planned to launch the campaign at the same time everywhere on the planet. That created unprecedented challenges for HEINEKEN—nowhere more so than in its technology operation. The primary digital content for the campaign was a 100-megabyte movie that had to play flawlessly for millions of viewers worldwide. After all, Bond never fails. No one was going to tolerate a technology failure that might bruise his brand.Previously, HEINEKEN had supported digital media at its outsourced datacenter. But that datacenter lacked the computing resources HEINEKEN needed, and building them—especially to support peak traffic that would total millions of simultaneous hits—would have been both time-consuming and expensive. Nor would it have provided the geographic reach that HEINEKEN needed to minimize latency worldwide.
Case Study
Energy Management System at Sugar Industry
The company wanted to use the information from the system to claim under the renewable energy certificate scheme. The benefit to the company under the renewable energy certificates is Rs 75 million a year. To enable the above, an end-to-end solution for load monitoring, consumption monitoring, online data monitoring, automatic meter data acquisition which can be exported to SAP and other applications is required.
Case Study
Coca Cola Swaziland Conco Case Study
Coco Cola Swaziland, South Africa would like to find a solution that would enable the following results: - Reduce energy consumption by 20% in one year. - Formulate a series of strategic initiatives that would enlist the commitment of corporate management and create employee awareness while helping meet departmental targets and investing in tools that assist with energy management. - Formulate a series of tactical initiatives that would optimize energy usage on the shop floor. These would include charging forklifts and running cold rooms only during off-peak periods, running the dust extractors only during working hours and basing lights and air-conditioning on someone’s presence. - Increase visibility into the factory and other processes. - Enable limited, non-intrusive control functions for certain processes.
Case Study
Temperature Monitoring for Restaurant Food Storage
When it came to implementing a solution, Mr. Nesbitt had an idea of what functionality that he wanted. Although not mandated by Health Canada, Mr. Nesbitt wanted to ensure quality control issues met the highest possible standards as part of his commitment to top-of-class food services. This wish list included an easy-to use temperature-monitoring system that could provide a visible display of the temperatures of all of his refrigerators and freezers, including historical information so that he could review the performance of his equipment. It also had to provide alert notification (but email alerts and SMS text message alerts) to alert key staff in the event that a cooling system was exceeding pre-set warning limits.
Case Study
Coca-Cola Refreshments, U.S.
Coca-Cola Refreshments owns and manages Coca-Cola branded refrigerators in retail establishments. Legacy systems were used to locate equipment information by logging onto multiple servers which took up to 8 hours to update information on 30-40 units. The company had no overall visibility into equipment status or maintenance history.
